1. Technical Field of the Invention
The present invention relates generally to an animal identification system designed to identify animals such as horse or cattle using biometric analysis, and more particularly to an automatic animal identification system based on analysis of irial granules which are unique for each individual.
2. Background Art
Typically, horse identification is achieved by visually perceiving physical features such as the color of hair or a pattern of white hair on the head or the body. Automatic identification systems have also been proposed which are designed to read identification data stored in a microchip embedded in the body of a horse.
For personal identification, automatic biometric systems are known which identify a particular human being based on image analysis of an iris of the human eye. Such techniques are taught in, for example, "High Confidence Visual Recognition of Persons by a Test of Statisical Independence", J. G. Daugman (1993), IEEE Trans and "Pattern Analysis and Machine Intelligence", 15(11), pp. 1148-1161.
Usually, animals such as horses or cattle have a three-dimensional protrusion called an irial granule, located around the pupil in the crystalline lens. The irial granule has a shape that is unique for each individual. Identification of animals such as horses or cattle can, thus, be performed based on analysis of the texture or shape of the irial granule.
The irial granule is, however, complex in shape and it is difficult to represent an outline of the irial granule using a geometric function having several parameters. Specifically, it is difficult for the conventional identification techniques as taught in the above references to extract the outline of the irial granule as image data.
The image of an eye captured by a videocamera in the open air may lack uniformity due to the use of an illuminator for the camera or entrance of external light, thus resulting in irregularity of image brightness of each of the pupil, the iris, and the irial granule or in dimness of the outline of the irial granule. A difficulty is, thus, encountered in extracting the outline of the irial granule through simple binary-coding or edge detection of the image.